Analysis of angular-differential postprocessing algorithms for exoplanet direct detection with a Photonic Lantern Nuller

Exoplanet research is essential for understanding planetary formation and the potential for life beyond our solar system. The direct imaging method captures exoplanet light while minimizing light from the host star. This is conventionally achieved with a coronagraph, which allows detailed characterization of planetary atmospheres and features. The Photonic Lantern Nuller (PLN) is an innovative instrument designed for the direct detection of closely orbiting exoplanets within the inner working angle of standard coronagraphs. Unlike traditional coronagraphs, where the planet’s signal is usually rotationally invariant, with the same point-spread-function at different position angles, and which also overlaps minimally with the residual stellar signal, data from a PLN consist of a one-dimensional collection of points that do not have rotational invariance and overlap significantly with the residual starlight arising from wavefront errors. Exploiting angular diversity to subtract these stellar residuals with the PLN thus requires adapting the angular differential imaging (ADI) technique for use with nonrotationally invariant planet signals at close separations, where strong self-subtraction effects occur. We reformulate ADI using principal component analysis to develop a method to extract spatial parameters of exoplanets from simulated one-dimensional PLN data. We test two variations of ADI on simulated data and show that injecting an antiplanet signal before stellar estimation helps localize the planet due to self-subtraction at lower separations.